Device and method for determining biological indicator levels in tissue

ABSTRACT

A device configured to determine a biological indicator level in tissue. The device includes at least one emitter configured to emit light, a detector configured to receive light and transmit data representative of the received light and a processor coupled to the at least one emitter and the detector. The device further includes a non-transitory storage medium coupled to the processor and configured to store instruction to cause the device to determine a level of a biological indicator.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims benefit to U.S. Provisional ApplicationNo. 62/166,571 filed May 26, 2015, the entire contents of which areincorporated by reference.

FIELD

The present disclosure relates to a non-invasive device to monitorbiological indicators in tissue or blood vessels, and more specificallypertains to an apparatus and method to determine a change in abiological indicator level.

BACKGROUND

Monitoring exertion via a heart rate monitor has long been a centerpieceof training for professional and performance athletes, as well asamateurs and retired players. Additional tests can be performed on theindividual and involve taking measurements of the individual by aprofessional. For example, some methods involve drawing of blood fromthe individual. Specifically, in order to measure total hemoglobin(tHb), the individual has blood drawn and tests performed to determinethe tHb level in the blood.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the advantages and features ofthe disclosure can be obtained, reference is made to the appendeddrawings. The drawings presented provide only non-limiting examples ofwhat is disclosed herein.

FIG. 1 is a schematic diagram of a non-invasive optical-electronicdevice, according to an example of the present disclosure.

FIG. 2A is a schematic diagram of the front of a non-invasiveoptical-electronic device, according to an example of the presentdisclosure.

FIG. 2B is a schematic diagram of the back of a non-invasiveoptical-electronic device, according to an example of the presentdisclosure.

FIG. 2C is a schematic diagram of a spatially-resolved NIRS sensor thatis included on a non-invasive optical-electronic device, according to anexample of the present disclosure.

FIG. 3 illustrates the components of an optical-electronic device,according to an example of the present disclosure.

FIG. 4 illustrates an environment within which the noninvasiveoptical-electronic device can be implemented, according to an example ofthe present disclosure.

FIG. 5A is a flowchart describing a method of generating calibrationfactors used to convert detected light data into optical densities,according to an example of the present disclosure.

FIG. 5B is a flowchart describing a method of generating calibrationfactors, using one or more objects with known optical densities, forconverting detected light data into optical densities, according to anexample of the present disclosure.

FIG. 6 is a flowchart describing a spectral projection algorithm used tocalculate indices from spectral data, according to an example of thepresent disclosure.

FIG. 7 is a flowchart describing an algorithm for user-specificadjustment of calculated indices, according to an example of the presentdisclosure.

FIG. 8 is a flowchart describing an adaptive algorithm for user-specificadjustment of SmO₂ calculation during a user activity, according to anexample of the present disclosure.

FIG. 9 is a plot illustrating Percentage (%) of Saturation SmO₂ versustime (s) for a user, calculated according to an example of the presentdisclosure.

FIG. 10 is a plot illustrating Percentage (%) of Saturation SmO₂ versustime (s) for a user using the same test protocol used to collect thedata shown in FIG. 9, but with an increased number of stages, accordingto an example of the present disclosure.

FIG. 11 is a plot of heart rate data corresponding to the plot ofPercentage of Saturation of SmO₂ in FIG. 10, according to an example ofthe present disclosure.

FIG. 12 is a plot illustrating an example of the projection method tocalculate total hemoglobin concentration, according to an example of thepresent disclosure.

FIG. 13A is a plot corresponding to SmO₂ values calculated without usingthe A and B parameters determined using a lactate threshold (LT)assessment activity, according to an example of the present disclosure.

FIG. 13B is a plot showing SmO₂ data that was calculated using the A andB parameters according to the algorithm described in FIG. 8, accordingto an example of the present disclosure.

FIG. 14 is a plot comparing user SmO₂ values calculated according to avector projection method (bottom) and a direction cosine method (top),according to an example of the present disclosure.

FIG. 15 is a plot comparing user Percentage (%) of Saturation SmO₂values calculated according to a pseudo-inverse projection method(bottom) and a vector projection method (top), according to an exampleof the present disclosure.

FIG. 16A is a plot demonstrating that the direct concentration method ofcalculating a biological indicator is affected by blood volume changes(dashed arrow) caused by arm occlusion, according to an example of thepresent disclosure.

FIG. 16B is a plot demonstrating a smaller blood volume changedependence for the data calculated using the spectral projectionmethods, for both the vector projection method (bottom) andpseudo-inverse method (top), according to an example of the presentdisclosure.

FIG. 17A is a plot illustrating an example of residual signaldetermination configured to detect interference over time, according toan example of the present disclosure.

FIG. 17B is a plot illustrating Percentage of Saturation over time,where the time scale is the same as that of FIG. 17A.

FIG. 18A is a plot illustrating a close-up view of the event at 555seconds, shown in FIG. 17A, according to an example of the presentdisclosure.

FIG. 18B is a plot illustrating Percentage of Saturation over time,where the time scale is the same as that of FIG. 18A.

FIG. 19A is a plot illustrating the relative change in heart rate overtime of a user during an assessment, according to an example of thepresent disclosure.

FIG. 19B is a plot illustrating the relative change in power output overtime of a user during the assessment of FIG. 19A.

FIG. 19C is a plot illustrating the relative change in hydration indexof a user during the assessment of FIG. 19A.

FIG. 20A is a plot illustrating the relative change in hemoglobin indexduring the same assessment shown in FIG. 19A.

FIG. 20B is a plot illustrating the relative change in hemoglobinconcentration during the same assessment shown in FIG. 19A.

FIG. 21A is an exploded view of a calibration container, according to anexample of the present disclosure.

FIG. 21B is a top perspective view of an interior portion of acalibration container, according to an example of the presentdisclosure.

FIG. 21C is a perspective view of exterior portions of a calibrationcontainer, according to an example of the present disclosure.

FIG. 21D is a cross-sectional view of a calibration container, accordingto an example of the present disclosure.

DETAILED DESCRIPTION

Various examples of the disclosure are discussed in detail below. Whilespecific implementations are discussed, it should be understood thatthis is done for illustration purposes only. A person skilled in therelevant art will recognize that other components and configurations canbe used without parting from the spirit and scope of the disclosure.

It should be understood at the outset that although illustrativeimplementations of one or more examples are illustrated below, thedisclosed devices, methods, and systems can be implemented using anynumber of techniques. The disclosure should in no way be limited to theillustrative implementations, drawings, and techniques illustratedherein, but can be modified within the scope of the appended claimsalong with their full scope of equivalents.

Unless otherwise specified, any use of any form of the terms “couple,”or “attach,” or any other term describing an interaction betweenelements is not meant to limit the interaction to direct interactionbetween the elements and also can include indirect interaction betweenthe elements described. The term “tissue” as used herein refers to anyof the distinct types of material of which animals or plants are made ofincluding specialized cells and their products. In the followingdiscussion and in the claims, the terms “including” and “comprising” areused in an open-ended fashion, and thus should be interpreted to mean“including, but not limited to . . . ”. As used herein, the term“spacing” refers to the distance between an emitter and a detector. Thevarious characteristics described in more detail below, will be readilyapparent to those skilled in the art with the aid of this disclosureupon reading the following detailed description, and by referring to theaccompanying drawings.

The present disclosure generally relates to a non-invasiveoptical-electronic device configured to determine a level of opticaldensity of different materials and, in particular, biological indicatorswithin tissue or blood vessels. Examples of non-invasiveoptical-electronic devices configured to determine biological indicatorsare described in U.S. Pat. No. 8,996,088 entitled APPARATUS AND METHODFOR IMPROVING TRAINING THRESHOLD, the entire contents of which areincorporated herein by reference. The optical-electronic device can beused by itself or in combination with other optical-electronic devicesor biosensors. The optical-electronic device can be configured todetermine physiological parameters of a user during exercise. It is tobe understood, however, that the non-invasive optical-electronic devicecan also be used in other applications without departing from theprinciples of the present disclosure, including microcirculationanalysis, newborn perfusion deficit, assessment of hemorrhage and shock,monitoring of fluid resuscitation, cognitive studies, cerebraloxygenation monitoring during cardiothoracic procedures, muscularoxygenation monitoring to diagnose acute and chronic compartmentsyndrome, and the monitoring of coronary artery disease (CAD) and othercardiovascular diseases.

The present disclosure generally relates to a device configured tomeasure physiological parameters of a user. In at least one example, thedevice can be a non-invasive optical electronic device. In one example,an optical-electronic device is configured to determine the level ofoptical density of a material, in particular biological indicatorswithin tissues or blood vessels using Near Infrared Spectroscopy (NIRS).The device includes a processor which calculates a relative matchbetween a spectral data set representative of received light and apredetermined spectral data set of one or more chromophores. Theoptical-electronic device can be configured to transmit an alert to anoutput device. The optical-electronic device can be further configuredto communicate a level of a biological indicator to a user in real-time.

In a further example, an optical-electronic device is configured todetermine the level of a biological indicator within tissues or bloodvessels, which is further configured to alert a user to the existence ofextraneous factors which interfere with the identification and/ordetermination of one or more biological indicators. The device candetermine the existence of an extraneous factor by determining a modulusof a residual of the fit of a projection onto a matrix containing thespectra representative of a predetermined data set of one or morechromophores. The device can also determine the existence of anextraneous factor by determining the relative match of a spectral dataset representative of received light and the null space for a matrixcontaining the spectra representative of a predetermined data set of oneor more chromophores.

In a further example, an optical-electronic device is configured todetermine the level of one or more biological indicators during exerciseand other physical conditions.

In another example, a method is configured to determine the level of oneor more biological indicators using an optical-electronic deviceconfigured to determine the level of a biological indicator withintissues or blood vessels using Near Infrared Spectroscopy (NIRS). Themethod includes calculating a relative match between a spectral data setrepresentative of received light and a predetermined spectral data setof one or more chromophores. The method can further include transmittingan alert to an output device. The method can further includecommunicating a level of a biological indicator to a user in real-time.

In another example, a method is configured to determine the level of abiological indicator within tissue or vessels. The method includesemitting light into a tissue, detecting the light, and transmitting datarepresentative of the received reflected light. The method can alsoinclude processing the data representative of the received reflectedlight with a processor having a non-transitory storage medium configuredto store instructions to cause the processor to receive the datarepresentative of the received reflected light. The method can alsoinclude comparing, via a processor, the data representative of thereceived reflected light to a predetermined spectral data set of one ormore chromophores corresponding to a biological indicator. The methodcan also include calculating, via a processor, a relative match betweenthe data representative of the received reflected light to thepredetermined spectral data set. The method can also include estimating,via a processor, a level of a biological indicator based on thecalculated relative match. The method can also include transmitting, viathe processor, the level of a biological indicator to an output device.The method can also include transmitting, via a processor, an alert toan output device.

In another example, a calibration method includes converting opticaldata into a parameter corresponding to the attenuation properties of abiological tissue. The method includes generating a calibration factorto convert detected light into optical densities for a given lightintensity, optical power, or optical irradiance, which can be based on acurrent, voltage, or using neutral density filters. The method can alsoinclude emitting light from at least two emitters into a tissue, wherethe at least two emitters are separated by a known distance.Additionally, the at least two emitters can have different knownspacings from the detector. The method can include receiving detectedlight data from the tissue at a photodetector. The method can alsoinclude receiving current data from the tissue at a electrocardiography(EKG) sensor. The method can also include converting detected light datainto optical densities for a given light intensity, or optical power oroptical irradiance (hereinafter referred to as intensity) using thecalibration factor. The method can include converting the opticaldensities into effective attenuation coefficients using opticaldensities determined from light data received from the two emittersseparated by a known distance, and therefore have different knownspacings from the detector. The method can also include converting theeffective attenuation coefficients into absorption coefficients using areduced scattering coefficient obtained for the tissue being monitored,where the absorption coefficient corresponds to the attenuationproperties of the tissue.

In a further example, a method can be used to determine a level of abiological indicator in a tissue. The method can be based on thecalibration optical data. The method includes generating a calibrationfactor to convert detected light into optical densities for a givenintensity, emitting light from at least two emitters into a tissue,where the two emitters are separated by a known distance, and thereforehave different known spacings from the detector. The method can alsoinclude converting detected light data into optical densities for agiven intensity using the calibration factor. The method can includeconverting the optical densities into effective attenuationcoefficients. The method can also include converting the effectiveattenuation coefficients into absorption coefficients using a reducedscattering coefficient obtained for the tissue being monitored, wherethe absorption coefficient corresponds to the attenuation properties ofthe tissue, and using the relative match of the absorption coefficientto predetermined spectral data to determine the level of a biologicalindicator in the tissue. The method can further include communicating alevel of a biological indicator to a user in real-time.

According to at least one example of the present disclosure, a device isconfigured to generate a calibration factor for use in determiningoptical density. The device includes at least one emitter having atleast one light source. In one example, the light source of the emittercan be a light emitting diode (LED) or any type of light sourceincluding lasers, laser diodes, vertical cavity surface emitting lasers(VCSEL) and light filtered from broadband sources, which include halogenlamps. In at least one example, all of the light sources can be an LED.An LED is an effective light source for the present disclosure since theLED has a dominate wavelength and the light intensity can be varied bythe current. LEDs are also widely available and economical. Lasers(including laser diodes, edge emitting lasers, external cavity lasers,gas lasers, crystal lasers and VCSELs) have the benefit of emitting at anarrow band of wavelengths. The emitter is configured to emit light. Thedevice further includes a detector configured to receive light andtransmit data representative of the received light. The device alsoincludes a processor coupled to the at least one emitter and thedetector. The device further includes a non-transitory storage mediumcoupled to the processor and configured to store instructions to causethe device to emit light from the at least one light source of the atleast one emitter at a predetermined intensity towards an object thathas a known optical density, detect, at the detector, a portion of theemitted light corresponding to the predetermined intensity, calculate,at the processor, a corresponding calibration factor based on thedetected portion of emitted light through the object, and store thecorresponding calibration factor in the non-transitory storage medium.

In a further example, the device further includes a non-transitorystorage medium having instructions to cause, repeatedly for each lightsource and each of a plurality of predetermined intensities, the deviceto emit light from one of the at least one light source of the at leastone emitter at one of the plurality of predetermined intensities towardsthe object, detect, at the detector, a portion of the emitted lightcorresponding to the predetermined intensity, calculate, at theprocessor, a corresponding calibration factor based on the detectedportion of emitted light through the object, and store the correspondingcalibration factor in the non-transitory storage medium.

In a further example, the at least one emitter includes a plurality ofemitters with each of the plurality of emitters having a plurality oflight sources. In a further example, the device further includes anon-transitory storage medium having instructions to cause the device toemit light, towards the object, from one of the plurality of lightsources of one of the emitters at one of a plurality of predeterminedintensities, detect, at the detector, a portion of the emitted lightcorresponding to the one of a the plurality of predeterminedintensities, calculate, at the processor, a corresponding calibrationfactor based on the detected portion of emitted light through theobject, and store the corresponding calibration factor in thenon-transitory storage medium.

In a further example, the device further includes at least two emitterseach comprising at least one light source. In a further example, thedevice further includes a non-transitory storage medium havinginstructions causing the processor to repeat the following for eachlight source: emit light, towards the object, from one light source ofone of the emitters at a predetermined intensity; detect, at thedetector, a portion of the emitted light corresponding to thepredetermined intensity; calculate, at the processor, a correspondingcalibration factor based on the detected portion of emitted lightthrough the object; and store the corresponding calibration factor inthe non-transitory storage medium.

In a further example, the predetermined intensity comprises a pluralityof intensities and each of the steps are performed for each of theplurality of intensities. In a further example, the at least twoemitters are spaced at different distances from the detector. In afurther example, the device further includes a non-transitory storagemedium having instructions to cause the device to confirm that acalibration factor is stored for each light source at the plurality ofintensities. In at least one example, the intensities can be based on apredetermined current. In a further example, the calculation of thecorresponding calibration factor is derived using the formula:C_(ijm)=10^(ODjm)/D_(ijm), where i is an index tracking a lightintensity value, which in at least one example is a predeterminedcurrent value, j is an index tracking a light source, m is an indextracking a spacing between the light source and detector, OD is theoptical density, and D is measured light data. In other examples asindicated above, the light intensity value can be any one of a current,voltage, or using neutral density filters.

In a further example, the non-transitory storage medium further includesinstructions, upon receiving a measurement command, to: emit,iteratively, light from one of a plurality of light sources at one of aplurality of predetermined intensities towards the object of interest;detect, at a detector, a portion of the emitted light corresponding to arespective one the light sources and predetermined intensities;determine an optical density of the object of interest based on thecalibration factors.

In a further example, the corresponding calibration factor istransmitted via a network interface component to a server. In a furtherexample, the corresponding calibration factor is transmitted via anetwork interface component to an external electronic device. In afurther example, the object is made of a material that is designed tomimic a biological tissue (that is, with reduced scattering andeffective attenuation coefficients in the range of those of biologicaltissue within the range of wavelengths spanned by the light sources). Ina further example, the at least one emitter comprises at least twoemitters that are spaced apart from each other and from the detector. Ina further example, one of the emitters is further away from the detectorthan the other. In a further example, each of the emitters are arrangedalong a ray extending from the detector. In a further example, each ofthe emitters are located on the same side of the detector. In a furtherexample, each of the two emitters include a plurality of LEDs or lightsources. In a further example, each of the two emitters includes fourLEDs or light sources. In a further example, each of the plurality ofLEDs or light sources within a given one of the least two emitters has adifferent peak wavelength of emission.

According to at least one example of the present disclosure, a methodfor calculating at least one calibration factor for an electronic deviceis configured to generate output data regarding a biological indicator.In at least one example, a set of calibration factors can be generatedsuch that there is a calibration factor that corresponds to eachcombination of illuminator, spacing, and intensity combination.Additionally, as described below, the set of calibration factors canalso consider the object from which the calibration factors are basedsuch that there are different sets corresponding to the differentobjects. The method includes emitting light from each one of a pluralityof light sources of at least one emitter at a first one of a pluralityof predetermined intensity, detecting, at a detector, a portion of theemitted light corresponding to the first predetermined intensity,calculating, at the processor, a corresponding calibration factor basedon the detected portion of emitted light, and storing the correspondingcalibration factor in the non-transitory storage medium.

In a further example, the method further includes repeatedly, for theremaining ones of the plurality of predetermined intensities: emittinglight from each one of the plurality of light sources of the at leastone emitter; detecting, at a detector, a portion of the emitted light;calculating, at the processor, a corresponding calibration factor basedon the detected portion of emitted light; and storing the correspondingcalibration factor in the non-transitory storage medium.

In a further example, the predetermined intensity comprises a pluralityof intensities and each of the steps are performed for each of theplurality of intensities. In a further example, the at least twoemitters are spaced at different distances from the detector. In afurther example, the method further includes confirming that acalibration factor is stored for each light source at the plurality ofpredetermined intensities. In at least one example, the plurality ofpredetermined intensities are based on a plurality of predeterminedcurrents. In a further example, the calculation of the correspondingcalibration factor is derived using the formula:C_(ijm)=10^(ODjm)/D_(ijm), where i is an index tracking a predeterminedlight intensity value, which can be a current value, j is an indextracking a light source, m is an index tracking a spacing between thelight source and detector, OD is the optical density, and D is measuredlight data. In other examples as indicated above, the light intensityvalue can be any one of a current, voltage, or using neutral densityfilters.

In a further example, the method further includes emitting, iteratively,light from one of a plurality of light sources at one of a plurality ofpredetermined intensities towards the object of interest, detecting, ata detector, a portion of the emitted light corresponding to a respectiveone the light sources and predetermined intensities, and determining anoptical density of the object of interest based on the calibrationfactors. In a further example, the method can further includetransmitting the corresponding calibration factor via a networkinterface component to a server. In a further example, the method caninclude transmitting the corresponding calibration factor via a networkinterface component to a server. In a further example, the object ismade of a material that is designed to mimic a biological tissue.

In a further example, the at least one emitter comprises at least twoemitters that are spaced apart from each other and from the detector. Ina further example, one of the emitters is further away from the detectorthan the other. In a further example, each of the emitters can bearranged along a ray extending from the detector. In a further example,each of the emitters can be located on the same side of the detector. Ina further example, each of the two emitters can include a plurality ofLEDs or light sources. In a further example, each of the two emittersincludes four LEDs or light sources. In a further example, each of theplurality of LEDs or light sources within a given one of the least twoemitters has a different peak wavelength of emission.

According to at least one example of the present disclosure, a systemincluding an electronic device and a hardware server is configured togenerate a calibration factor for use in determining optical density.The system includes at least one emitter having at least one lightsource, the emitter configured to emit light. The system can furtherinclude a detector configured to receive light and transmit datarepresentative of the received light. The system can also include aprocessor coupled to the at least one emitter and the detector. Thesystem can further include a non-transitory storage medium coupled tothe processor and configured to store instructions to cause the deviceto emit light from the at least one light source of the at least oneemitter at a predetermined intensity towards an object that has a knownoptical density, detect, at the detector, a portion of the emitted lightcorresponding to the predetermined intensity, calculate, at theprocessor, a corresponding calibration factor based on the detectedportion of emitted light through the object, and store the correspondingcalibration factor in the non-transitory storage medium.

In a further example, the at least one emitter, the detector, theprocessor, and the non-transitory storage medium are located within theelectronic device. In a further example, the at least one emitter, thedetector, and the processor are located within the electronic device andthe non-transitory storage medium is located within the server.

According to at least one example of the present disclosure, a methodfor calculating a calibration factor for an electronic device isconfigured to generate output data regarding an optical density. Themethod includes placing, iteratively, the electronic device on one of aplurality of objects, each having a known optical density, emitting,iteratively, light from one of a plurality of light sources at one of aplurality of predetermined intensities, detecting, at a detector, aportion of the emitted light corresponding to a respective one of theplurality of objects, light sources, and predetermined intensities,calculating, at the processor, a corresponding calibration factor basedon the detected portion of emitted light, storing the correspondingcalibration factor in the non-transitory storage medium, and determiningthat the non-transitory medium has a corresponding calibration factorfor each combination of the plurality of objects, light sources, andpredetermined intensities, wherein the calibration factors are stored ina plurality of matrices, each of the plurality of matrices correspondingto one of the plurality of objects.

In a further example, the method further includes generating a matrix ofbest fit calibration factors based on a linear fit of the plurality ofmatrices. In a further example, the method further includes placing theelectronic device on an object of interest, emitting, iteratively, lightfrom one of a plurality of lights sources at one of a plurality ofpredetermined intensities, detecting, at a detector, a portion of theemitted light corresponding to a respective one of the plurality ofobjects, light sources, and predetermined intensities, and determiningan optical density of the object of interest based on the matrix of bestfit calibration factors.

According to at least one example of the present disclosure, a devicecan be configured to generate a calibration factor for use indetermining optical density. The device includes a plurality of lightsources, each configured to emit light. The device can further include adetector configured to receive light and transmit data representative ofthe received light. The device can further include a processor coupledto the plurality of light sources and the detector. The device can alsoinclude a non-transitory storage medium coupled to the processor andconfigured to store instructions to cause the device to iteratively emitlight from one of the plurality of LED at one of a plurality ofpredetermined intensity towards one of a plurality of objects, each ofthe plurality of objects having a known optical density, detect, at thedetector, a portion of the emitted light, calculate, at the processor, acorresponding calibration factor based on the detected portion ofemitted light through the object, store the corresponding calibrationfactor in the non-transitory storage medium, and determine that thenon-transitory medium has a corresponding calibration factor for eachcombination of the plurality of objects, light sources, andpredetermined intensities.

According to at least one example of the present disclosure, acalibration container can include a main body forming a through openingconfigured to receive a test sample on one side and an electronic deviceon another side. The electronic device is configured to emit light froma plurality of emitters and receive light at a detector. The calibrationcontainer can further include an upper lid coupled to the main body andconfigured to securely enclose the one side. The calibration containercan also include an object having known optical properties. In otherexamples, the object can be obtained separately from the calibrationcontainer. The calibration container can further include a lower lidcoupled to the main body and configured to securely enclose the anotherside. The calibration container can also include a first gasketconfigured to be mounted between the main body and the upper lid and asecond gasket configured to be mounted between the main body and thelower lid.

In a further example, the calibration container can further include asupport plate configured to hold the electronic device in closeproximity to the object. In a further example, the support plate formsat least three through holes corresponding to locations of the pluralityof emitters and the detector. In a further example, the support plate iscoupled to the main body via a plurality of threaded connections.

In a further example, the calibration container can further include alower elastic material that is coupled to lower lid and configured topress the object against the support plate. In a further example, themain body forms a first gasket groove, which is configured to receive aportion of the first gasket. In a further example, the main body forms asecond gasket groove, which is configured to receive a portion of thesecond gasket.

In a further example, the lower lid is coupled to the main body via aplurality of threaded connections, thereby holding the object within themain body. In a further example, the main body forms a first and secondsupport ledge configured to support the electronic device on a firstside and a second side. In a further example, the calibration containercan further include an upper elastic material coupled to the upper lidand configured to hold the electronic device in place against the firstsupport ledge and the second support ledge. In a further example, thecalibration container further includes a hinge configured to couple theupper lid to the main body. In a further example, the calibrationcontainer further includes a latch configured to releasably secure theupper lid to the main body. In a further example, the main body has aportion configured to receive the object.

In another example, a method is presented that determines auser-specific measure of a biological indicator in a tissue using apredetermined set of user-specific parameters. The method includesgenerating a set of user-specific parameters based on that user'sbiological indicator data collected during an assessment using anoptical-electronic device configured to capture optical data of atissue. The method can also include storing the set of user-specificparameters on a server. The method can include measuring a biologicalindicator in the tissue of the user during a physical activity using anoptical-electronic device configured to capture optical data of atissue. The method can also include calculating a user-specific measureof the biological indicator using the set of user-specific parametersstored on the server. The method can further include transmitting analert to an output device, wherein the alert is configured to notify theuser of a user-specific measure of a biological indicator. The methodcan further include communicating a level of a biological indicator to auser in real-time.

In a further example, a method is described for determining auser-specific measure of Total Oxygenation Index (TOI) in a tissue usingpredetermined user-specific lactate threshold (LT) assessment data. Themethod includes generating user-specific TOI data while performing a LTassessment using an optical-electronic device configured to captureoptical data of a tissue. The method further includes calculatinguser-specific TOI adjustment parameters. The method can also includestoring the LT assessment based user-specific TOI adjustment parameterson a server. The method can include measuring TOI in the tissue of theuser during a physical activity using the optical-electronic device. Themethod can also include calculating a user-specific measure of TOI usingthe user specific TOI adjustment parameters stored on the server. Themethod can further include transmitting an alert to an output device,wherein the alert is configured to notify the user of a user-specificmeasure of TOI. The method can further include communicating auser-specific measure of TOI to a user in real-time.

According to at least one example of the present disclosure, a device isconfigured to determine a biological indicator. The device can includeat least two emitters having at least one light emitting element, the atleast two emitters configured to emit light. The device further includesa detector configured to receive light and transmit data representativeof the received light. The device also includes a processor coupled tothe emitter and the detector and a non-transitory storage medium coupledto the processor. The non-transitory storage medium can be configured tostore instructions to cause the device to emit a first light from one ofthe at least two emitters at a first predetermined intensity, detect atleast a portion of the of first emitted light at the detector, obtain afirst calibration factor, from the non-transitory storage medium,corresponding to the first predetermined intensity, generate a firstoptical density corresponding to the first calibration factor, emit asecond light from another one of the at least two emitters at the firstpredetermined intensity, detect at least a portion of the second emittedlight at the detector, obtain a second calibration factor, from thenon-transitory storage medium corresponding to the first predeterminedintensity, generate a second optical density corresponding to the secondcalibration factor, convert the first and second optical density to aneffective attenuation coefficient based on the separation of the oneemitter and the another emitter, and generate a biological indicatorfrom the effective attenuation coefficient.

In a further example, the device further includes a non-transitorystorage medium that also includes instructions causing the processor tocalculate a relative match between the detected light and apredetermined spectral data set of one or more chromophorescorresponding to the biological indicator, and estimate a level of thebiological indicator based on the calculated relative match. In afurther example, the relative match is calculated between the detectedlight and the predetermined spectral data set representative of the oneor more chromophores using one or more of inner products, vectorprojections, direction cosines, and a pseudo-inverse projection method.In a further example, an effective attenuation coefficient, μ_(eff), iscalculated according to the equation μ_(eff)=0.192 ΔOD−0.098, whereΔOD=OD_(far)−OD_(near), where OD_(far) is the optical densitycorresponding to emitter spaced farther from the detector and theOD_(near) is the optical density corresponding to the emitter spacednearer the detector. The optical density can be calculated for eachemitter according to OD_(jm)=log₁₀(C_(ijm)×D_(ijm)), where C_(ijm) isthe calibration factor and D_(ijm) is the detected light at lightintensity i, wavelength j, and distance m. In a further example in whichthe predetermined spectral data set is an absorption coefficient, thedetected light is converted from an effective attenuation coefficientinto the absorption coefficient by combining it with a known reducedscattering coefficient. In other examples as indicated above, the lightintensity value can be any one of a current, voltage, or using neutraldensity filters.

In a further example, a modulus of a residual of a fit of a projectiononto a matrix containing a spectra representative of a predetermineddata set of one or more chromophores is determined. In a furtherexample, the relative match of a spectral data set representative ofreceived light and a null space for a matrix containing the spectrarepresentative of a predetermined data set of one or more chromophoresis determined. In a further example, the one or more chromophoresincludes one or more of hemoglobin, myoglobin, cytochrome c, water,lipids, melanins, glucose or metabolites. In a further example,hemoglobin includes at least one of oxyhemoglobin, deoxyhemoglobin, andtotal hemoglobin. In a further example, the total hemoglobin and thewater is further utilized to determine perfusion characteristics of oneor more of hemoglobin concentration, pulsatile rhythm, blood volume,vascular tone, muscular tone, and angiogenesis. In a further example,myoglobin comprises at least one of oxymyoglobin, deoxymyoglobin, andtotal myoglobin. In a further example, metabolites include at least oneof lactate and lactic acid. In a further example, the one or morechromophores includes water and the water is further utilized to measurea hydration level.

In a further example, the device further includes a non-transitorystorage medium further configured to store instructions to cause theprocessor to calculate a relative ratio of the one or more chromophores.In a further example, the non-transitory storage medium is furtherconfigured to store instructions to cause the processor to calculate arelative addition of the one or more chromophores. In a further example,the non-transitory storage medium is further configured to storeinstructions to cause the processor to extract data associated with theone or more chromophores from data representative of the detected light.In a further example, the at least two emitters are configured to emitat least three wavelengths of light or at least three ranges ofwavelengths. In a further example, the biological indicator comprises atleast one of a relative percentage, a saturation level, an absoluteconcentration, a rate of change, an index relative to trainingthreshold, and a threshold.

According to at least one example of the present disclosure, a method isconfigured to determine a biological indicator. The method includesemitting a first light from one of at least two emitters at a firstpredetermined intensity, detecting at least a portion of the firstemitted light at a detector, obtaining a first calibration factor, fromthe non-transitory storage medium, corresponding to the predeterminedintensity, generating a first optical density corresponding to the firstcalibration factor, emitting a second light from another one of the atleast two emitters at the first predetermined intensity, detecting atleast a portion of the second emitted light at the detector, obtaining asecond calibration factor, from the non-transitory storage medium,corresponding to the predetermined intensity, generating a secondoptical density corresponding to the second calibration factor,converting the first and second optical density to an effectiveattenuation based on the separation of the one emitter and the anotheremitter, and generating a biological indicator from the effectiveattenuation.

FIG. 1 illustrates a non-invasive optical-electronic device 100,according to an example of this disclosure. The device 100 can beattached to a portion, such as a muscle mass, of a user via a strap 115.The device 100 can be used with an optional output device 150, such as asmartphone (as shown), a smart watch, computer, mobile phone, tablet, anelectronic processing and displaying unit, cloud storage, or a remotedata repository via a cellular network or wireless Internet connection.

The device 100 includes a sensor 125 that is configured to determine thelevel of a biological indicator within tissue or blood vessels usingNIRS. The sensor 125 includes an optical emitter 105 and an opticaldetector 110. In general, the sensor 125 uses two or more low-powerlasers, LEDs or quasi-monochromatic light sources and low-noisephotodetecting electronics to determine the optical absorption ofchromophores, such as water, hemoglobin in its multiple forms, includingoxyhemoglobin (HbO₂), deoxyhemoglobin (HHb), oxymyoglobin,deoxymyoglobin, cytochrome c, lipids, melanins, lactate, glucose,myoglobin (including myoglobin at least one of oxymyoglobin,deoxymyoglobin, and total myoglobin) or metabolites. The metabolites caninclude at least one of lactate and lactic acid. Cytochrome c can beused, for example, to track muscle adaptation to training. In anotherexample, the sensor 125 can use a broad-spectrum optical source and adetector sensitive to the spectral components of light, such as aspectrometer, or a charge-coupled device (CCD) or other linearphotodetector coupled with near-infrared optical filters.

The optical-electronic device 100 can be configured to include a secondsensor 135 configured to measure photoplethysmography (PPT) of the user.The second sensor 135 includes an optical emitter 145 and an opticaldetector 146. The device 100 also includes a third sensor 175 configuredto measure electrocardiography (EKG) and derived systolic time intervals(STI) of the user. The third sensor 175 includes a first electrode 180and a second electrode 181. The sensors 125, 135, 175 in the device 100can measure NIRS parameters, electrocardiography, photoplethysmography,and derived systolic time intervals (STI) of the user. Theoptical-electronic device 100 also includes a processor that isconfigured to analyze data generated by the sensors 125, 135, 175 todetermine a cardiac response to exercise and the supply, arteriovenousdifference, utilization of oxygen by the muscle tissue and hydration ofthe muscular tissue.

In at least one example, the processor is configured to determinebiological indicators, including, but not limited to a relativepercentage, a saturation level, an absolute concentration, a rate ofchange, an index relative to a training threshold, and a threshold. Inother cases, the processor is configured to determine perfusioncharacteristics such as pulsatile rhythm, blood volume, vascular tone,muscle tone, and angiogenesis from total hemoglobin and watermeasurements.

The device 100 can include a power supply, such as a battery, to supplypower to the sensors 125, 135, 175 and other components in the device100. In one example, the sensor 125 has a skin contact area of 3.5″×2″.In other examples, the sensor 125 can be sized to fit on the forearm ofa user. In still other examples, the sensor 125 can be sized to fit onthe wrist of the user.

FIG. 2 illustrates a non-invasive optical-electronic device 200,according to an alternative example of this disclosure. The device 200is configured to be worn on a limb of a user, such as on the calf muscleof a user's leg or the bicep of a user's arm. In at least one example,the device 200 can be optimized for a given limb, thereby increasingaccuracy of the device. In other examples, the device 200 can beoptimized based on the size, gender, or age of the user. In still otherexamples, a variety of the above optimizations can be implemented for agiven device. FIG. 2A illustrates the front of the optical-electronicdevice. FIG. 2B illustrates the back of the optical-electronic device,including emitters 220, 230, 250 and photodetector 210. The device 200also includes data and charging contacts 270. In at least one example,the data and charging contacts 270 can be used to electrically detect ifthe sensor is making contact with the skin of a user. The presence ofmultiple emitters 220, 230, 250 on the optical-electronic device allowsfor spatially-resolved data gathering in real-time. Theoptical-electronic device 200 can be configured to determine the opticalabsorption of chromophores, such as water, hemoglobin in its multipleforms, including oxyhemoglobin (HbO₂), deoxyhemoglobin (HHb),oxymyoglobin, deoxymyoglobin, cytochrome c, lipids, melanins, lactate,glucose, or metabolites.

FIG. 2C illustrates a spatially-resolved NIRS sensor that can beincluded on the non-invasive optical-electronic device 200, according toan example of the disclosure. As shown in FIG. 2C, thespatially-resolved NIRS sensor includes light emitters 280 and 281 whichemit light that is scattered and partially absorbed by the tissue. Eachemitter 280, 281 can be configured to emit a single wavelength of lightor a single range of wavelengths. In at least one example, each emitter280, 281 can be configured to emit at least three wavelengths of lightor at least three ranges of wavelengths. Each emitter 280, 281 caninclude one or more LEDs or light sources. Each emitter 280, 281 caninclude a low-powered laser, LED, or a quasi-monochromatic light sourceas a light source, or any combination thereof. Each emitter 280, 281 canalso include a light filter.

A fraction of the light emitted by emitters 280 and 281 is detected byphotodetector 285, as illustrated by the parabolic or “banana shaped”light arcs 291 and 292. Emitters 280, 281, are separated by a knowndistance 290, and therefore have different known spacings 295, 296 fromthe detector 285, and produce a signal that is later detected atphotodetector 285. The detected signal is used to estimate the effectiveattenuation and absorption coefficients of the underlying tissue asdescribed later in FIG. 6, for example at blocks 640 and 650. In atleast one example, the known distance 290 between emitters 280, 281 is12 millimeters. In at least one example, the 12 millimeter knowndistance between emitters 280 and 281 corresponds to a known spacing 295of emitter 281 from detector 285 of 27 millimeters and a known spacing296 of emitter 280 from detector 285 of 15 millimeters. In otherexamples, the known distance can be selected based on a variety offactors, which can include the wavelength of the light, the tissueinvolved, or the age of the user. While FIG. 2C depicts emitters 280,281 arranged in a row and longitudinally spaced such that known distance290 corresponds to a difference in the spacing between emitters 280, 281and photodetector 285, the emitters can be spaced in any configurationso long as at least two of the emitters are spaced at differentdistances from photodetector 285.

The optical-electronic device 200 disclosed herein can have differentnumbers of emitters and photodetectors without departing from theprinciples of the present disclosure. Further, the emitters andphotodetectors can be interchanged without departing from the principlesof the present disclosure. Additionally, the wavelengths produced by thelight sources can be the same for each emitter or can be different.

In at least one example, the device 200 is used for the monitoring ofphysiological parameters of a user during a physical activity. Use ofthe device 200 can be relevant in endurance type sports, such asrunning, cycling, multisport competition, rowing, but can also be usedin other physical activities. The device 200 can be configured towirelessly measure real-time muscle parameters during physical exercise.The device 200 can be secured to a selected muscle group of the user,such as the leg muscles of the vastus lateralis or gastrocnemius, whichare primary muscle groups of running and cycling.

FIG. 3 illustrates the components of an optical-electronic device 300according to an example of this disclosure. As shown in FIG. 3, theoptical-electronic device includes an emitter 310 and detector 320,which are coupled to a processor 330. The processor 330 is coupled to anon-transitory storage medium 340. The device 300 is coupled to anoutput device 390.

The emitter 310 delivers light to the tissue and the detector 320collects the optically attenuated signal that is back-scattered from thetissue. In at least one example, the emitter 310 can be configured toemit at least three separate wavelengths of light. In another example,the emitter 310 can be configured to emit at least three separate bandsor ranges of wavelengths. In at least one example, the emitter 310 caninclude one or more light emitting diodes (LEDs) or light sources. Theemitter 310 can also include a light filter. The emitter 310 can includea low-powered laser, LED, or a quasi-monochromatic light source, or anycombination thereof, as a light source. The emitter can emit lightranging from infrared to ultraviolet light. As indicated above, thepresent disclosure uses NIRS as a primary example and the other types oflight can be implemented in other examples and the description as itrelates to NIRS does not limit the present disclosure in any way toprevent the use of the other wavelengths of light.

The data generated by the detector 320 can be processed by the processor330, such as a computer processor, according to instructions stored inthe non-transitory storage medium 340 coupled to the processor. Theprocessed data can be communicated to the output device 390 for storageor display to a user. The displayed processed data can be manipulated bythe user using control buttons or touch screen controls on the outputdevice 390.

The optical-electronic device 300 can include an alert module 350configured to generate an alert. The processor 330 can send the alert tothe output device 390 or the alert module 350 can send the alertdirectly to the output device 390. In at least one example, theoptical-electronic device 300 can be configured so that the processor330 is configured to send an alert to the output device 390 without thedevice including an alert module 350.

The alert can provide notice to a user, via a speaker or display on theoutput device 390, of a change in biological indicator conditions orother parameter being monitored by the device 300, or the alert can beused to provide an updated biological indicator level to a user. In atleast one example, the alert can be manifested as an auditory signal, avisual signal, a vibratory signal, or combinations thereof. In at leastone example, an alert can be sent by the processor 330 when apredetermined biological indicator event occurs during a physicalactivity.

In at least one example, the optical-electronic device 300 can include aGlobal Positioning System (GPS) module 360 configured to determinegeographic position and tagging the biological indicator data withlocation-specific information. The optical-electronic device 300 canalso include a thermistor 370 and an inertial measurement unit (IMU)380. The inertial measurement unit (IMU) 380 can be used to measure, forexample, gait performance of a runner or pedal kinematics of a cyclist,as well as physiological parameters of a user during a physicalactivity. The thermistor 370 and inertial measurement unit (IMU) 380 canalso serve as independent sensors configured to independently measureparameters of physiological threshold. The thermistor 370 and inertialmeasurement unit (IMU) 380 can also be used in further algorithms toprocess or filter the optical signal.

FIG. 4 illustrates an environment within which the noninvasiveoptical-electronic device 400 can be implemented, according to anexample of this disclosure. As shown in FIG. 4, the optical-electronicdevice 400 is worn by a user to determine biological indicator levelsduring a physical activity. The optical-electronic device 400 isdepicted as being worn on the calf of a user 405, however, theoptical-electronic device 400 can be worn on any portion of the usersuitable for monitoring biological indicator levels. The device 400 canbe used with an output device 410, such as a smartphone (as shown), asmart watch, computer, mobile phone, tablet, an electronic processingand displaying unit, cloud storage, or a remote data repository via acellular network or wireless Internet connection.

As shown in FIG. 4, the optical-electronic device 400 communicates witha output device 410 so that data collected by the optical-electronicdevice 400 is displayed or transferred to the output device 410 forcommunication of real-time biological indicator data to the user 405. Inat least one example, an alert can be communicated from the device 400to the output device 410 so that the user 405 can be notified of abiological indicator event. Communication between the device 400 and theoutput device 410 can be via a wireless technology, such as BLUETOOTH®,infrared technology, or radio technology, or can be through a wire.Transfer of data between the optical-electronic device 400 and theoutput device 410 can also be via removable storage media, such as asecure digital (SD) card. In at least one example, a display unit can besubstituted for the output device 410.

The optical-electronic device 400 also communicates with a personalcomputing device 440 or other device configured to store and/or displayuser-specific biological indicator data. The personal computing device440 can include a desktop computer, laptop computer, tablet, smartphone,smart watch, or other similar device. Communication between the device400 and the personal computing device 440 can be via a wirelesstechnology, such as BLUETOOTH®, infrared technology, or radiotechnology. In other examples, the communication between the device 400and the personal computing device 440 can be through a wire or otherphysical connection. Transfer of data between the optical-electronicdevice 400 and the personal computing device 440 can also be viaremovable storage media, such as an SD card.

The output device 410 can communicate with a server 430 via a network420, allowing transfer of user-specific biological indicator data to theserver 430. The output device 410 can also communicate user-specificbiological indicator data to cloud-based computer services orcloud-based data clusters via the network 420. The output device 410 canalso synchronize user-specific biological indicator data with a personalcomputing device 440 or other device configured to store or displayuser-specific biological indicator data. The output device 410 can alsosynchronize user-specific biological indicator data with a personalcomputing device 440 or other device configured to both store anddisplay user-specific biological indicator data. Alternatively, thepersonal computing device 440 can receive data from a server 430 orcloud-based computing service via the network 420.

The personal computing device 440 can communicate with a server 430 viaa network 420, allowing the transfer of user-specific biologicalindicator data to the server 430. The personal computing device 440 canalso communicate user-specific biological indicator data to cloud-basedcomputer services or cloud-based data clusters via the network 420. Thepersonal computing device 440 can also synchronize user-specificbiological indicator data with the output device 410 or other deviceconfigured to store and/or display user-specific biological indicatordata.

The optical-electronic device 400 can also directly communicate data viathe network 420 to a server 430 or cloud-based computing and datastorage service. In at least one example, the device 400 can include aGPS module configured to communicate with GPS satellites (not shown) toobtain geographic position information.

The optical-electronic device 400 can be used by itself or incombination with other optical-electronic devices or biosensors. Forexample, the optical-electronic device 400 can be used in combinationwith heart rate (HR) biosensor devices, foot pod biosensor devices,and/or power meter biosensor devices. The optical-electronic device 400can also be used in combination with ANT+™ wireless technology anddevices that use ANT+™ wireless technology. The optical-electronicdevice 400 can be used to aggregate data collected by other biosensorsincluding data collected by devices that use ANT+™ technologies.Aggregation of the biosensor data can be via a wireless technology, suchas BLUETOOTH®, infrared technology, or radio technology, or can bethrough a wire.

The biosensor data aggregated by the optical-electronic device 400 canbe communicated via a network 420 to a server 430 or to cloud-basedcomputer services or cloud-based data clusters. The aggregated biosensordata can also be communicated from the optical-electronic device 400 tothe output device 410 or personal computing device 440.

In at least one example, the optical-electronic device 400 can employmachine learning algorithms by comparing data collected in real-timewith data for the same user previously stored on a server 430, outputdevice 410, or in a cloud-based storage service. The machine learningalgorithm can also be performed on or by any one of the output device410, cloud-based computer service, server 430, or personal computingdevice 440, or any combination thereof.

According to this disclosure, determination of the level of a biologicalindicator within tissue or blood vessels is achieved by calculating arelative match, or indices, between the spectral data received at thedetector with a predetermined spectral data set of one or morechromophores corresponding to the biological indicator. In at least oneexample, the predetermined spectral data set corresponds to the signalspectra of specific analytes that can be readily obtained from theliterature. See for example, Analyt. Biochem. Vol 227, pp. 54-68 (1995).The relative match calculation is performed by calculating a projectionof the spectral data set captured from a user in the direction of thepredetermined spectral data set in order to calculate an index thatreflects the proximity of the match. The spectral projection method canbe used to calculate a relative percentage level of a biologicalindicator or, with proper calibration, can be used to calculate theabsolute concentration of a biological indicator.

The spectral projection method of determining the level of a biologicalindicator can be implemented mathematically using the inner productmethod which will be explained, by way of example, using the TotalOxygenation Index (TOI) as the biological indicator of interest. TOI isthe ratio of the oxygenated hemoglobin (HbO₂) to total hemoglobin (tHb),where total hemoglobin (tHb) is equal to the combined concentrations ofthe oxygenated hemoglobin (HbO₂) and the chromophore deoxygenatedhemoglobin (HHb):

TOI=[HbO₂]/[tHb] or TOI %=100*([HbO₂]/[tHb]), where [tHb]=[HbO₂]±[HHb].

TOI, as used herein, includes the more specific parameter, SmO₂, whichis the muscle oxygen saturation. SmO₂ can also be the tissue oxygensaturation determined from optical measurements of muscle tissue. Bothoxygenated hemoglobin (HbO₂) and deoxygenated hemoglobin (HHb) arechromophores for which a spectral data set can be predetermined. Thenotation O(D) can be used to denote the predetermined spectral data foroxyhemoglobin (deoxyhemoglobin) at the same wavelengths for which thespectral data set for a user was measured at the detector, and U can beused to denote the measured data set, including an effective attenuation(μ_(eff)) or an effective absorption coefficient (μ_(a)). The innerproduct method of calculating the spectral projection can be calculatedaccording to different mathematical methods, including, but not limitedto, a direction cosine method, vector projection method, and apseudo-inverse projection method:

Direction Cosine Method:

${{TOI} = \frac{\langle{U,O}\rangle}{\langle{U,{O + {D\sqrt{\frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}}}}}\rangle}},$

Vector Projection Method:

${{TOI} = \frac{\langle{U,O}\rangle}{\langle{U,{O + {D\frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}}}}\rangle}},$

Pseudo-Inverse Projection Method:

${TOI} = {\frac{\langle{U,{O - {\frac{\langle{O,D}\rangle}{\langle{D,D}\rangle}D}}}\rangle}{\langle{U,{{O\left\lbrack {1 - \frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}} \right\rbrack} + {D\left\lbrack {\frac{\langle{O,O}\rangle}{\langle{D,D}\rangle} - \frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}} \right\rbrack}}}\rangle}.}$

All of these methods can be rewritten as

${TOI} = \frac{\langle{U,{O - {aD}}}\rangle}{\langle{U,{{O\left( {1 - a} \right)} + {D\left( {b - a} \right)}}}\rangle}$

-   -   where a and b are scalars defined as i) a=0,

${b = \sqrt{\frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}}};$

ii) a=0,

${b = \frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}};$

and iii)

$a = {{\frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}\mspace{14mu} {and}\mspace{14mu} b} = \frac{\langle{O,O}\rangle}{\langle{D,D}\rangle}}$

for the cosine, vector projection and pseudo-inverse methods,respectively.

Prior to calculating indices, calibration coefficients can be generatedwhich allow the indices calculation to be corrected for the absorptionproperties of the tissue. FIGS. 5A and 5B are flowcharts describingmethods used to generate the calibration coefficients that can be used,for example, by the projection indices algorithm.

Referring to FIG. 5A, a flowchart is presented in accordance with anexample. The example method shown in FIG. 5A is provided by way of anexample, as there are a variety of ways to carry out the method. Eachblock shown in FIG. 5A represents one or more processes, methods, orsubroutines, carried out in the example method shown in FIG. 5A.Furthermore, the illustrated order of blocks is illustrative only andthe order of the blocks can change according to the present disclosure.Additional blocks can be added or fewer blocks can be utilized, withoutdeparting from this disclosure.

The example calibration method can begin at block 500. At block 510, theoptical-electronic device can be attached, located in close proximity,or otherwise situated adjacent to an object with known absorbancesOD_(jm). In at least one example, the object can be a phantom, which hasbeen configured with special optical properties. In one example, thespecial optical properties can be that to resemble tissue. While phantomis used herein, other objects are considered within the scope of thepresent disclosure. This procedure is repeated for each spacing m atblock 520 and for each light source or light source wavelength, j, atblock 530. At block 540, all light intensities, i, are swept. At block550, light data D_(ijm) are captured. The calibration factors arecalculated at block 560, using the formula: C_(ijm)=10^(ODjm)/D_(ijm).In other examples as indicated above, the light intensity can be any oneof a current, voltage, or using neutral density filters.

Block 570 determines whether the calibrations algorithm has beenrepeated for each light source. If the calibration has not beenperformed for one or more light sources the blocks beginning with block540 are repeated for the additional light source until all light sourceshave been calibrated. Block 575 determines whether the calibration hasbeen performed for all separation distances between the emitters and adetector. If it is determined that calibration has not been performedfor all distances between the emitters and a detector, the blocksbeginning with block 530 are repeated until the last light source andlast spacing has been calibrated, upon which the calibration factors arestored in block 580. Calibration factors C_(ijm) are stored on a serverand/or the firmware in block 585. The calibration algorithm is completedin block 590. The calibration factors stored according to the methoddescribed in FIG. 5A, can be used, for example, by the projectionindices algorithm shown in FIG. 6.

The phantom used in the method described in FIG. 5A can be any suitablesolid phantom, including, but not limited to optical-grade qualitypolymers that simulate a wide variety of tissues in the VIS-NIR. In atleast some instances, the phantom can comprise a polymer, a scatteringagent, and a light absorbing dye. In at least some instances, thepolymer can be, but is not limited to, polyurethane or apolyurethane-based polymer. The scattering agent can be, but is notlimited to titanium dioxide (TiO₂). The absorbing dye can be, but is notlimited to, carbon black. In some instances, the phantom can comprise apolyurethane-based polymer further including a scattering agent and anabsorbing dye. In at least some instances, the phantom can be aBiomimic™ Optical Phantom available from INO of Quebec, Canada(www.ino.ca).

The phantom can be manufactured to have predetermined light scatteringand light absorption characteristics. For example, the phantom can bemanufactured to have a predetermined absorption coefficient (μ_(a)) at areference wavelength and/or a predetermined scattering coefficient(μ_(s)′) at a reference wavelength. For example, the predetermined lightscattering and light absorption characteristics of the phantom can beengineered by changing the amount of scattering agent and absorbing dyein the polymer phantom. In at least some instances, the method describedin FIG. 5A can further include selecting a phantom having a lightabsorption and light scattering characteristics that mimic the tissuefor which the optical electronic device will determine a biologicalindicator.

Referring to FIG. 5B, a flowchart is presented in accordance with anexample. The example method shown in FIG. 5B is provided by way of anexample, as there are a variety of ways to carry out the method. Eachblock shown in FIG. 5B represents one or more processes, methods, orsubroutines, carried out in the example method shown in FIG. 5B.Furthermore, the illustrated order of blocks is illustrative only andthe order of the blocks can change according to the present disclosure.Additional blocks can be added or fewer blocks can be utilized, withoutdeparting from this disclosure.

FIG. 5B provides an example calibration method that can be used forcalibrating an optical-electronic device having one or more emitters,each having one or more LEDs, spaced from a detector by differentspacings. The example calibration method provided in FIG. 5B includesplacing in proximity or otherwise adjacent the optical-electronic deviceto one or more objects having a known optical density. In one example,the optical-electronic device can be attached to one or more objectshaving a known optical density. While a single object having a knownoptical density is sufficient to perform the calibration, using multipleobjects having a known optical density can, at least in some instances,provide an improved set of calibration factors. According to the methodprovided in FIG. 5B, each calibration using an object having a knownoptical density provides a separate set of calibration factors, thusallowing the determination of a best-fit set of calibration factors,that may be determined, for example, by calculating a linear regression.Thus, the method of FIG. 5B, in at least some instances, provides forminimization of error between the set of calibration factors and thetrue calibration factors.

The example calibration method can begin at block 505. At block 505, theoptical-electronic device can be attached, located in close proximity,or otherwise situated adjacent to an object with a known optical densityOD_(jm). At block 515, a value corresponding to the spacing, m, of anemitter from a detector on the optical-electronic device is obtained. Atblock 525, light having wavelength, j, is emitted from a light source ofan emitter, at one or more predetermined light intensity, i, towards theobject having a known optical density. A portion of the emitted lightcorresponding to the one or more predetermined light intensities,D_(ijm), is detected at a detector at block 535. In other examples asindicated above, the light intensity value can be any one of a current,voltage, or using neutral density filters.

At block 545, a corresponding calibration factor based on the detectedportion of emitted light through the object is calculated using theformula: C_(ijm=)10^(ODjm)/D_(ijm). The corresponding calibration factoris stored on the device or on a server at block 555. Block 565determines whether calibration blocks 525 to 555 have been performed foreach light source of an emitter. If calibration blocks 525 to 555 havenot been performed for one or more light sources of an emitter, theblocks beginning with block 525 are repeated for the additional lightsource until calibration has been performed for all light sources of anemitter.

Block 566 determines whether calibration blocks 515 to 555 have beenperformed for each emitter. If it is determined that calibration blocks515 to 555 have not been performed for all emitters, the blocksbeginning with block 515 are repeated until calibration has beenperformed for all emitters. Thus, the method provides for calibration ofeach emitter which each emitter potentially having a unique spacingdistance between the emitter and the detector.

Block 567 determines whether calibration blocks 505 to 555 have beenperformed for each object having a known optical density. If it isdetermined that calibration blocks 505 to 555 have not been performedfor each object having a known optical density, the blocks beginningwith block 505 are repeated until calibration has been performed for allobjects having a known optical density. As previously described, themethod described in FIG. 5B may be performed using only a single objecthaving a known optical density. However, the use of multiple objects,each having a different known optical density can allow, at least insome instances, for the optical-electronic device to be accurately usedwithin a wider range of materials.

In instances in which multiple objects having different known opticaldensities are used, calibration blocks 505 to 567 produce S sets ofcalibration factors C_(ijm), where S is the number of calibrationobjects employed. Then, once the last object having a known opticaldensity is calibrated, a linear fit between the calibration factorsC_(ijm) and the optical densities OD_(jm) is performed at block 568,resulting in the best fit calibration factors C_(ijm). The best fitcalibration factors can then be stored on the device or on a server oroutput as a calibration matrix at block 569. In instances in which onlya single object having a known optical density is used, the calibrationfactors C_(ijm) can be output to a calibration matrix, at block 569,comprising the calculated calibration factors, without performing block568. The calibration factors C_(ijm) stored according to the methoddescribed in FIG. 5B, can be used, for example, by the projectionindices algorithm shown in FIG. 6.

The object having a known optical density used in the method describedin FIG. 5B can be any suitable solid object having known opticalproperties, including, but not limited to optical-grade quality polymersthat simulate a wide variety of tissues in the VIS-NIR. In at least someinstances, the object having a known optical density can comprise apolymer, a scattering agent, and a light absorbing dye. In at least someinstances, the object having a known optical density can be, but is notlimited to, polyurethane or a polyurethane-based polymer. The scatteringagent can be, but is not limited to titanium dioxide (TiO₂). Theabsorbing dye can be, but is not limited to, carbon black. In someinstances, the objecting having a known optical density can comprise apolyurethane-based polymer further including a scattering agent and anabsorbing dye. In at least some instances, the object having a knownoptical density can be a Biomimic™ Optical Phantom available from INO ofQuebec, Canada (www.ino.ca).

In at least some instances, the method described in FIG. 5B can furtherinclude selecting an object having a known optical density that hasoptical characteristics that mimic the tissue for which the opticalelectronic device will determine a biological indicator. In otherinstances, the method described in FIG. 5B may be performed usingmultiple objects having known optical density. In such instances, themethod can further include selecting the objects having known opticaldensities to have optical properties that mimic the optical propertiesof the range of human tissues in the VIS-NIR spectra for which theoptical electronic device will determine a biological indicator. Forexample, the object or objects having a known optical density can bemanufactured to have predetermined light scattering and light absorptioncharacteristics. More specifically, the objects or objects having aknown optical density can be manufactured to have a predeterminedabsorption coefficient GO at a reference wavelength and/or apredetermined scattering coefficient (μ_(s)′) at a reference wavelength.For example, the predetermined light scattering and light absorptioncharacteristics of an object having a known optical density can beengineered by changing the amount of scattering agent and absorbing dyein the polymer that comprises the object having a known optical density.

Referring to FIG. 6, a flowchart is presented in accordance with anexample. The example method shown in FIG. 6 is provided by way of anexample, as there are a variety of ways to carry out the method. Eachblock shown in FIG. 6 represents one or more processes, methods, orsubroutines, carried out in the example method shown in FIG. 6.Furthermore, the illustrated order of blocks is illustrative only andthe order of the blocks can change according to the present disclosure.Additional blocks can be added or fewer blocks can be utilized, withoutdeparting from this disclosure.

FIG. 6 describes a spectral projection algorithm used to calculateindices from spectral data. The example algorithm can begin at block600. At block 610, the optical-electronic device is identified and thecalibration factors C_(jm) are loaded onto the device. At block 620, thedetected light data D_(jm) is received by the device for a given lightintensity i. The detected light data are converted into opticaldensities for a given light intensity i using the calibration factorsC_(jm), at block 630, using the equation:OD_(jm)=log₁₀(C_(ijm)×D_(ijm)). In other examples as indicated above,the light intensity value can be any one of a current, voltage, or usingneutral density filters.

At block 640, the optical densities are converted to effectiveattenuations using optical densities determined from at least twoemitters separated from the detector by a known distance. The slope ofthe optical density varies with respect to the effective attenuationaccording to the following expression:

${\frac{dOD}{dp} = {{\mu_{eff}\log_{10}e} + \frac{2}{\rho ln10}}},$

in which ρ denotes the distance between light source and detector.Accordingly, the effective attenuation can be determined from the slopeof the preceding expression. Alternatively, in an example in which thereare two different spacings, such as one emitter that is 15 millimetersfrom the detector and one emitter that is 27 millimeters from thedetectors, resulting in a distance between spacings of 12 millimeters,we have μ_(eff)(j)=0.192(OD_(j2)−OD_(j1))−0.098. At block 650, theeffective attenuations are converted to absorption coefficients,according to the equation:μ_(a)(j)=0.5[sqrt(μ_(s)′(j)²+4/3μ_(eff)(j)²)−μ_(s)′(j)], where μ_(s)′(j)is the reduced scattering coefficient for tissue being monitored, takenfrom the literature in block 645. For example, from Applied Optics, Vol.36, No. 1, pp. 386-396 (1997). The inner product is calculated at block660, according to the equation: P_(k)=Σ_(j)μ_(a)(j)Finv_(jk), whereFinv_(jk) is the pseudo-inverse of known absorption spectra atwavelengths j taken from the literature at block 655, and Σ_(j) denotessummation over index j. At block 670, the inner product, P_(k), obtainedfrom the previous block is processed using a low-pass filter anddisplayed on a mobile device or display at block 676 and/or sent to aserver for storage and transmission across a network at block 675.Additionally, saturations and thresholds are calculated at block 670 anddisplayed on a mobile device or display and/or sent to a server forstorage and transmission across a network. Block 670 further generatesan alarm, alert or notification based upon the calculated indices,saturations, and/or thresholds and displays the alarm, alert, ornotification on a mobile device or display. At block 680, the spectralprojection algorithm stops if the device is set to intermittentmonitoring or in the case of constant monitoring by spectral analysis,the blocks beginning with block 620, can be repeated. In at least oneexample, the spectral projection algorithm described in FIG. 6 can beused to display biological indicator data to a user in real-time.

Referring to FIG. 7, a flowchart is presented in accordance with anexample. The example method shown in FIG. 7 is provided by way of anexample, as there are a variety of ways to carry out the method. Eachblock shown in FIG. 7 represents one or more processes, methods, orsubroutines, carried out in the example method shown in FIG. 7.Furthermore, the illustrated order of blocks is illustrative only andthe order of the blocks can change according to the present disclosure.Additional blocks can be added or fewer blocks can be utilized, withoutdeparting from this disclosure.

FIG. 7 describes an algorithm for the generation of user-specificadjustment parameters and their use to provide personalized measurementsof biological indicators during the activity of a user. In FIG. 7, theinner product as a function of time, P_(k)(t), obtained from thespectral projection algorithm, is calculated during an assessmentactivity, giving rise to customized user-specific adjustment parametersA_(k)(t). A_(k)(t) is calculated based on prior knowledge of how itshould vary during a controlled exercise protocol, such as an assessmentactivity, thereby providing the algorithm with a user-specific set ofcustomized parameters P_(k)(t)′.

The assessment activity can begin at block 700. An example of anassessment activity that can be performed according to this disclosureis a Lactate Threshold (LT) assessment. However, it should be understoodby one skilled in the art that the present disclosure is equallywell-suited for use with other assessment activities, controlledexercise protocols, and with any biological indicators configured to bemeasured using the optical-electronic device. At block 710, an innerproduct of the biological indicator of interest is calculated as afunction of time. At block 720, user-specific adjustment parameters,such as Pk(t), and A_(k)(t) are calculated, thereby generating theuser-specific set of parameters, A_(k)(t), which are stored in theserver database and/or used to update the user-specific adjustmentparameters on the server at block 740. The A_(k)(t) values are then usedlater when the user wants to measure P_(k)(t)′, a more user specificversion of P_(k)(t), during a physical activity.

The physical activity can be begun by the user at block 750. At block755, activity data is collected. P_(k)(t) is calculated at block 760. Atblock 765, the P_(k)(t) values calculated at block 760, are adjustedusing the user-specific set of parameters stored at block 740(P_(k)(t)′=f[P_(k)(t), A_(k)(t)]). At block 770, the P_(k)(t)′ data isdisplayed to the user and stored on the server at block 775. Thisalgorithm, providing customized adjustment parameter monitoring to auser during a physical activity, continues until the user physicalactivity ends at block 785. The algorithm described in FIG. 7 can berepeated iteratively so as to routinely or constantly update theuser-specific adjustment parameters on the server in order to displayuser-specific biological indicator levels using the latest or mostup-to-date user-specific adjustment parameters. Additionally, learningalgorithms can be used which compare data collected in real-time withpreviously collected data for the same user stored on a server.

Referring to FIG. 8, a flowchart is presented in accordance with anexample. The example method shown in FIG. 8 is provided by way of anexample, as there are a variety of ways to carry out the method. Eachblock shown in FIG. 8 represents one or more processes, methods, orsubroutines, carried out in the example method shown in FIG. 8.Furthermore, the illustrated order of blocks is illustrative only andthe order of the blocks can change according to the present disclosure.Additional blocks can be added or fewer blocks can be utilized, withoutdeparting from this disclosure.

FIG. 8 describes an algorithm for adaptive SmO₂ calculation during auser activity, which can include any physical activity, for examplejogging, biking, running, swimming, or exercising. This SmO₂ algorithmis a special case of the algorithm for customized parameter monitoringdescribed in FIG. 7. SmO₂ is muscle oxygen saturation or tissue oxygensaturation determined from optical measurements of muscle tissue. SmO₂is equal to the ratio of the oxyhemoglobin level divided by the totalhemoglobin level, where the total hemoglobin level equals theoxyhemoglobin level plus the deoxyhemoglobin level. The algorithmdescribed in FIG. 8 uses data collected during a lactate threshold (LT)assessment activity to increase the accuracy of SmO₂ results, therebyproviding users with customized monitoring of SmO₂ values during aphysical activity. While the algorithm described in FIG. 8 relies on afixed offset of the oxyhemoglobin concentration, Oxy(t), and a fixedoffset of the deoxyhemoglobin concentration, Deoxy(t), data calculatedusing, for example, indices from the spectral projection algorithmdisclosed in FIG. 6, it should be understood by one skilled in the artthat the present disclosure is equally well-suited for use with anyother algorithm known to those skilled in the art, including but notlimited to the multi-variate Beer-Lambert method.

The LT assessment activity can begin at block 800. At block 810, SmO₂ iscalculated as a function of time. SmO₂ is calculated according to theequation: SmO₂=Oxy(t)/[Oxy(t)+Deoxy(t)]. At block 820, oxy offsets (A)and deoxy offsets (B) are calculated. At block 840, the A and B valuesare stored in a server database, or used to update the user-specific Aand B values stored on the server. The A and B values are then used toincrease the user specificity of SmO₂ determinations made during aphysical activity.

The physical activity can be begun by the user at block 850. At block855, activity data is collected. Oxy(t) and Deoxy(t) are calculated atblock 860. At block 865, SmO₂ values are adjusted using the A and B datastored at block 840 (SmO₂=[Oxy(t)+A]/[Oxy(t)+A+Deoxy(t)+B]). At block870, the SmO₂ data is displayed to the user and stored on the server atblock 875. This algorithm, providing more specific SmO2 monitoring for auser during a physical activity, continues until the user physicalactivity ends at block 885.

The algorithm described in FIG. 8 can be repeated iteratively so as toroutinely or constantly update the user-specific adjustment parameterson the server in order to display user-specific biological indicatorlevels using the latest or most up-to-date user-specific adjustmentparameters. Additionally, learning algorithms can be used which comparedata collected in real-time with previously collected data for the sameuser stored on a server.

FIG. 9 illustrates Percentage (%) of Saturation SmO₂ versus time (s),calculated according to the present disclosure, for a user running on atreadmill at a pace that increases every 180 s, with 30-second restperiods in between. As shown in FIG. 9, sharp peaks of oxygenation occurduring the resting periods, demonstrating that the algorithm correctlytracks the expected increase in oxygenation that takes place during theresting periods.

FIG. 10 illustrates Percentage (%) of Saturation SmO₂ versus time (s)for a user using the same test protocol used to collect the data shownin FIG. 9 but with an increased number of stages (eleven stages insteadof six stages). As shown in FIG. 10, the baseline signal drops after1200 seconds, indicating that the user's maximum Percentage (%)Saturation during exertion was achieved at that point.

FIG. 11 is a plot of heart rate data corresponding to the plot ofPercentage of Saturation of SmO₂ in FIG. 10, according to an example ofthe present disclosure. As shown in FIG. 11, the high oxygenation peaksare closely followed by drops in heart rate, as is expected to occurduring the resting periods.

FIG. 12 illustrates an example of the projection method to calculateindices, as disclosed herein, being used to measure total hemoglobin.The optical-electronic device was applied to the arm of the user. Venousocclusion is applied to the user's arm at 176 seconds, resulting in arapid increase in blood volume until 354 seconds, when the occlusion isremoved and the blood volume is rapidly reduced.

FIG. 13 shows the effect of determining user SmO₂ values adapted duringan activity using the algorithm described in the flowchart presented inFIG. 8. FIG. 13A shows a plot corresponding to SmO₂ values calculatedwithout using the A and B parameters determined using an LT assessment.FIG. 13B shows SmO₂ data that was calculated using the A and Bparameters according to the algorithm described in FIG. 8, that shiftsTOI down from a baseline of 100% and a range of 90-100% to a moreuser-specific baseline of 88% and a range of 65-88%.

FIG. 14 compares user SmO₂ values calculated according to a directioncosine method (top) and a vector projection method (bottom).

FIG. 15 compares user Percentage (%) Saturation SmO₂ values calculatedaccording to a pseudo-inverse projection method (bottom) and a vectorprojection method (top). The data was collected for a user wearing anoptical-electronic device on their left calf while running an intervaltraining session, consisting of running at a pace that increases every180 s, with 30-second rest periods in between, giving rise to anincrease in Percentage (%) of Saturation.

FIG. 16 compares Percentage (%) of Saturation data collected during anarm occlusion test, calculated according to the spectral projectionmethod (FIG. 16B) with a direct concentration measurement known in theart (FIG. 16A). As shown in FIG. 16A, the direct concentration method isaffected by blood volume changes (dashed arrow) caused by arm occlusion.By contrast, FIG. 16B demonstrates a smaller blood volume changedependence for the data calculated using the spectral projectionmethods, for both the vector projection method (bottom) andpseudo-inverse method (top).

In addition to demonstrating less sensitivity to blood volume changes,the spectral projection method of determining biological indicatorlevels is also less affected by other confounding factors not directlyrelated to chromophore tissue levels, including fat, melanin, scartissue, tattoos, hair, and clothing. The spectral projection method isalso less sensitive to factors that affect both paths of light equally,such as variations in temperature or ambient light. In the case of anoptical-electronic device that includes two or more emitters and asingle detector, the spectral projection method produces data that isless affected by variations in photodetector responsivity ortrans-impedance amplifier gain. In the case of an optical-electronicdevice configured to include a single emitter and two or morephotodetectors, the spectral projection method produces data that isless affected by variations in LED power and variations in spectrum.

The optical-electronic device, as disclosed herein, can also transmit asignal or an alert to an output device such as a user display or mobiledevice. One form of an alert can signal or flag the existence ofextraneous factors which interfere with the identification and/ordetermination of one or more biological indicators. The existence ofextraneous factors can be indicated by determining the relative match ofa spectral data set representative of received light and the null spacefor a matrix containing the spectra representative of a predetermineddata set of one or more chromophores, which is the set of vectors thatwill be mapped to 0 by the F matrix. As described at block 660 of FIG.6, the inner product is calculated as P_(k)=Σ_(j)μ_(a)(j)Finv_(jk),where P_(k) are the projections due to analyte k, and Finv is thepseudo-inverse of matrix F containing the spectra of the analytes atwavelengths j. The residual signal R is given by R=|u_(a)−P*F^(T)|,where T denotes the transpose, ∥ denotes magnitude, and * denotes matrixmultiplication. Accordingly, R represents the part of the detectedsignal that failed to project towards any of the analytes of interest.Under normal conditions, R remains low. However, under specialconditions, such as when clothing interferes with the optical-electronicdevice, an abrupt increase in the modulus of R would be expected. Whenthe modulus of R increases suddenly, or when it surpasses apre-determined threshold, an alarm can be conveyed to the user.Accordingly, the optical-electronic device can be configured to generatea null-space or residual signal to flag the existence of extraneousfactors, including, but not limited to: clothing, hair, tattoos, scartissue, melanin, fat, poor sensor placement, and motion-related factors.

FIG. 17A is a plot illustrating an example of residual signaldetermination configured to detect interference over time, according toan example of the present disclosure. FIG. 17B is a plot illustratingPercentage of Saturation over time, where the time scale is the same asthat of FIG. 17A. FIGS. 17A and 17B illustrates an example of residualsignal determination configured to detect interference. As shown inFIGS. 17A and 17B, the residual signal abruptly increased at 555 secondsindicating that the optical-electronic device monitored an unexpectedsignal. In this case, the abrupt change in residual signal was caused bysensor movement which in turn caused fabric to get in between one of thelight emitters and the tissue being monitored.

FIG. 18A illustrates a close-up view of the event at 555 seconds,showing a clear and abrupt increase in the residual signal from FIG.17A. FIG. 18B is a plot illustrating Percentage of Saturation over time,where the time scale is the same as that of FIG. 18A.

In this case, a threshold of about 4×10⁻⁶ would provide the user with analarm telling the user to check sensor placement, thereby increasing thereliability of the parameters being monitored by sensor and saving theuser from the frustration of collecting invalid data.

The provision of an alert in response to an extraneous factorinterfering the identification and determination of biologicalindicators is especially valuable to wearable athletic monitoring inwhich users move frequently using optical-electronic devices that can beinterwoven in fabric and therefore increases the robustness of theoptical-electronic device by providing a user with a clear indication ofthe occurrence of a problem.

FIG. 19A is a plot illustrating the relative change in over time of auser during an assessment, according to an example of the presentdisclosure. FIG. 19B is a plot illustrating the relative change in poweroutput over time of a user during the assessment of FIG. 19A. FIG. 19Cis a plot illustrating the relative change in hydration index of a userduring the assessment of FIG. 19A. As shown in FIGS. 19A-C, as the timeand exertion level increases over the course of the assessment protocol,the hydration level decreases, as would be expected due to increaseddiaphoresis and respiration. This is especially true close to the end ofthe assessment, when exertion levels are the highest.

FIG. 20A is a plot illustrating the relative change in hemoglobin indexduring the same assessment shown in FIGS. 19A-C. FIG. 20B is a plotillustrating the relative change in hemoglobin concentration during thesame assessment shown in FIGS. 19A-C. The change in total hemoglobinshown in FIG. 20B was calculated according to the pseudo-inverseprojection method. FIGS. 20A-B also shows that as more hemoglobinbecomes present in the capillaries of the muscle being monitored, thegastrocnemius muscle in this case, the higher the total hemoglobindetected by the optical-electronic device.

As shown in FIGS. 20A-B, as the user approaches exhaustion, the totalhemoglobin level starts to drop with a reduction in the level ofhydration. The hemoglobin concentration, on the other hand, remainsfairly constant after reaching a peak level around 800 seconds. Thehemoglobin concentration plot can be generated by taking the ratiobetween the total hemoglobin index and the relative hydration andmultiplying by a user-specific proportionality constant.

As shown in FIGS. 20A-B, the perfusion characteristics of muscle,including blood volume, pulsatile rhythm, vascular tone, muscular tone,and angiogenesis, can be monitored during an assessment by determiningtotal hemoglobin and hydration using the optical-electronic device.

In addition to the generation of an alarm or alert for non-biologicalinterference, the magnitude of the residual can be an indicator ofbiological interference. The residual can represent a real physiologicalsignal due to a change in one or more chromophores not quantified by theprojection onto the known list of chromophores. The set of vectorscorresponding to the null space of F can be used to postulate theexistence of another set of chromophores in the tissues being monitored.Further, the null space set of vectors can be used as a starting pointfor determining the identity of additional chromophores that can bemonitored.

According to at least one example of the present disclosure, thepresently disclosed optical-electronic device can be calibrated using acalibration container, such as that shown in FIGS. 21A-D. FIG. 21Aprovides an exploded view of an example calibration container 2100 thatis suitable for use in calibrating an electronic device 2110, such as,for example, any of the optical-electronic devices described in thepresent disclosure. For example, the calibration methods described withrespect to FIGS. 5A and 5B can, at least in some instances, be conductedusing one or more calibration containers, such as the calibrationcontainer shown in FIG. 21.

As depicted in FIG. 21A, the calibration container 2100 can include amain body 2105 forming a through opening 2115 configured to receive anobject having known optical properties 2130 on one side and anelectronic device 2110 on another side. The main body 2105, as well asother portions of the calibration container 2100, may comprise anysuitable material that is opaque to light, including, but not limitedto, Black DELRIN® (a type of polyoxymethylene) or black-anodizedaluminum. Additionally, the main body can be configured to block andabsorb light. In at least one example, a film can cover the main body toassist in the blocking and absorption of light. In at least someinstances, the object having known optical properties 2130 can be aphantom or an object having a known optical density such as thatdescribed with respect to FIGS. 5A and 5B. The calibration container2100 serves to contain the electronic device 2110 and the object havingknown optical properties 2130 securely together in a stable andlight-tight environment. In one example, the object can be included withthe calibration container 2100. In another example, the object can bepurchased separately or obtained from another source.

As depicted in FIG. 21A, the main body 2105 forms a first support ledge2106 and a second support ledge 2108 configured to support theelectronic device 2110 on a first side and a second side. The electronicdevice 2110 is configured to emit light from a plurality of emitters andreceive light at a detector. In at least some instances, the electronicdevice 2110 is a spatially-resolved light-emitting device.

The calibration container 2100 can include an upper lid 2145 coupledwith the main body 2105 and configured to securely enclose one side ofthe main body 2105. The upper lid 2145 is used to close the calibrationcontainer 2100 during calibration to prevent light from interfering withthe calibration measurements and method. The calibration container 2100can further include, in at least some instances, a hinge 2146 configuredto couple the upper lid 2145 to the main body 2105. The calibrationcontainer 2100 can also include a latch 2107 configured to releasablysecure the upper lid 2145 to the main body 2105. The latch 2107 alsofacilitates insertion and removal of the electronic device 2110 from thecalibration container 2100 and can in some instances provide for a moreconsistent positioning between the electronic device 2110 and the objecthaving known optical properties 2130.

The calibration container 2100 can further include a first gasket 2120configured to be mounted between the main body 2105 and the upper lid2145. As depicted in FIG. 21A, the main body 2105 forms a first gasketgroove 2102 configured to receive a portion of the first gasket 2120.The first gasket 2120 can help provide firm closure of the upper lid2145 to the main body 2105 while maintaining a light-tight seal duringcalibration of the electronic device 2110. In at least some instances,the calibration container 2100 can include an upper elastic material2148 coupled with the upper lid 2145. The upper elastic material 2148can be configured to hold the electronic device 2110 in place againstthe first support ledge 2106 and the second support ledge 2108. Theupper elastic material 2148 can be configured, at least in someinstances, to gently push the device down during the closing of upperlid 2145 to facilitate correct positioning and alignment of theelectronic device 2110 during calibration.

As depicted in FIG. 21A, the calibration container 2100 can furtherinclude a lower lid 2140 coupled to the main body 2105 and configured tosecurely enclose the other side of the main body 2105. The lower lid2140 is coupled with the object having known optical properties 2130 andencloses the object having known optical properties 2130 into a portionof the main body 2105, configured to receive the object having knownoptical properties 2130. In at least some instances, the lower lid 2140is coupled to the main body 2105 by a plurality of threaded connections2142, thereby securing the object having known optical properties 2130within the main body 2105.

As depicted in FIG. 21A, the calibration container 2100 can also includea second gasket 2135 configured to be mounted between the main body 2105and the lower lid 2140. In at least some instances, the main body 2105can form a second gasket groove configured to receive a portion of thesecond gasket. The second gasket 2135 forms a light-tight seal betweenthe lower lid 2140 and the main body 2105 after the lower lid 2140 issecured to the main body 2105. The calibration container 2100 canfurther include a support plate 2125 configured to hold the electronicdevice 2110 in close proximity to the object having known opticalproperties 2130. The support plate 2125 can comprise any suitablematerial, including, but not limited to, Black Black DELRIN® or anodizedaluminum. In at least some instances, the support plate 2125 forms atleast three through holes 2128 corresponding to locations of theplurality of emitters and the detector on the electronic device 2110.The through holes 2128 defines the apertures through which light canpropagate out from emitters on the electronic device 2110 toward andthrough the object with known optical properties 2130. The through holes2128 also define the aperture through which light can propagate toward adetector on the electronic device 2110 from the object with knownoptical properties 2130. In some instances, the support plate 2125 canbe coupled to the main body 2105 by a plurality of threaded connections2127.

In at least some instances, the calibration container 2100 can include alower elastic material 2143 coupled to the lower lid 2140. The lowerelastic material 2143 can be configured to press the object having knownoptical properties 2130 against the support plate. In at least someinstances, the lower elastic material 2143 facilitates correctpositioning and alignment of the object having known optical properties2130 in the main body 2105 during calibration of the electronic device2110.

FIG. 21B is a top perspective view of an interior portion of thecalibration container 2100 shown in FIG. 21A. FIG. 21B depicts thecalibration container 2100 with the upper lid 2145 open thereby showingmain body 2105 forming a through opening 2115 configured to receive anelectronic device 2110. The main body 2105 further forms a first supportledge 2106 and a second support ledge 2108 configured to support theelectronic device 2110 on a first side and a second side. Thecalibration container 2100 also includes a first gasket 2120 mounted onthe main body 2105 configured to provide firm closure of the upper lid2145 to the main body 2105 while maintaining a light-tight seal duringcalibration of the electronic device 2110. FIG. 21B also shows supportplate 2125 having three through holes 2128 corresponding to locations ofthe plurality of emitters and the detector on the electronic device2110. While three through holes 2128 are illustrated, the number ofthrough holes 2128 can vary. As illustrated, each of the through holes2128 correspond to one of the emitters or detector. In other examples, athrough hole 2128 can serve one or more emitters or detectors. Thethrough holes 2128 allows light from emitters on the electronic device2110 to propagate toward and through the object with known opticalproperties 2130.

FIG. 21C is a perspective view of the calibration container 2100 withthe upper lid 2145 closed to securely enclose the electronic device 2110and object having known optical properties 2130 inside the main body2105. The upper lid 2145 is used to close the calibration container 2100during calibration to prevent light from interfering with thecalibration measurements and method.

FIG. 21D is a cross-sectional view of the calibration container 2100showing the electronic device 2110 secured in the main body 2105 betweenthe upper lid 2145 and calibration block 2130. The support plate 2125provides through holes corresponding to the emitters and detector on theelectronic device 2110.

The examples shown and described above are only examples. Even thoughnumerous characteristics and advantages of the present technology havebeen set forth in the foregoing description, together with details ofthe structure and function of the present disclosure, the disclosure isillustrative only, and changes can be made in the detail, including inmatters of shape, size and arrangement of the parts within theprinciples of the present disclosure, up to, and including, the fullextent established by the broad general meaning of the terms used in theclaims.

What is claimed is:
 1. A device configured to determine a biologicalindicator, the device comprising: at least two emitters having at leastone light emitting element, the at least two emitters configured to emitlight; a detector configured to receive light and transmit datarepresentative of the received light; a processor coupled to the emitterand the detector; a non-transitory storage medium coupled to theprocessor and configured to store instructions to cause the device to:emit a first light from one of the at least two emitters at a firstpredetermined current; detect at least a portion of the first emittedlight at the detector; obtain a first calibration factor, from thenon-transitory storage medium, corresponding to the first predeterminedcurrent; generate a first optical density corresponding to the firstcalibration factor; emit a second light from another one of the at leasttwo emitters at the first predetermined current; detect at least aportion of the second emitted light at the detector; obtain a secondcalibration factor, from the non-transitory storage medium,corresponding to the first predetermined current; generate a secondoptical density corresponding to the second calibration factor; convertthe first and second optical density to an effective attenuationcoefficient based on a separation of the one emitter and the anotheremitter; determine a level of a biological indicator from the effectiveattenuation coefficient.
 2. The device as recited in claim 1, whereinthe non-transitory storage medium further comprises instructions causingthe processor to: calculate a relative match between the detected lightand a predetermined spectral data set of one or more chromophorescorresponding to the biological indicator; and estimate a level of thebiological indicator based on the calculated relative match.
 3. Thedevice as recited in claim 2, wherein the relative match is calculatedbetween the detected light and the predetermined spectral data setrepresentative of the one or more chromophores using one or more ofinner products, vector projections, direction cosines, and apseudo-inverse projection method.
 4. The device as recited in claim 2,wherein the effective attenuation coefficient is calculated from theequation: 0.192 OD−0.098, where ΔOD=OD_(far)−OD_(near), where OD_(far)is the optical density corresponding to emitter spaced farther from thedetector and the OD_(near) is the optical density corresponding to theemitter spaced nearer the detector.
 5. The device as recited in claim 2,wherein the predetermined spectral data set is an absorptioncoefficient, and wherein the detected light is converted from aneffective attenuation coefficient into the absorption coefficient bycombining it with a known reduced scattering coefficient.
 6. The deviceas recited in claim 5, wherein a modulus of a residual of a fit of aprojection onto a matrix containing a spectra representative of apredetermined data set of one or more chromophores is determined.
 7. Thedevice as recited in claim 5, wherein the relative match of a spectraldata set representative of received light and a null space for a matrixcontaining the spectra representative of a predetermined data set of oneor more chromophores is determined.
 8. The device as recited in claim 2,wherein the one or more chromophores comprises one or more ofhemoglobin, myoglobin, cytochrome c, water, lipids, melanins, glucose ormetabolites.
 9. The device as recited in claim 8, wherein hemoglobincomprises at least one of oxyhemoglobin, deoxyhemoglobin, and totalhemoglobin.
 10. The device as recited in claim 9, wherein the totalhemoglobin and the water is further utilized to determine perfusioncharacteristics of one or more of hemoglobin concentration, pulsatilerhythm, blood volume, vascular tone, muscular tone, and angiogenesis.11. The device as recited in claim 8, wherein myoglobin comprises atleast one of oxymyoglobin, deoxymyoglobin, and total myoglobin.
 12. Thedevice as recited in claim 8, wherein metabolites comprises at least oneof lactate and lactic acid.
 13. The device as recited in claim 2,wherein the one or more chromophores comprises water and the water isfurther utilized to measure a hydration level.
 14. The device as recitedin claim 2, wherein the non-transitory storage medium is furtherconfigured to store instructions to cause the processor to calculate arelative ratio of the one or more chromophores.
 15. The device asrecited in claim 2, wherein the non-transitory storage medium is furtherconfigured to store instructions to cause the processor to calculate arelative addition of the one or more chromophores.
 16. The device asrecited in claim 2, wherein the non-transitory storage medium is furtherconfigured to store instructions to cause the processor to extract dataassociated with the one or more chromophores from data representative ofthe detected light.
 17. The device as recited in claim 1, wherein the atleast two emitters are configured to emit at least three wavelengths oflight or at least three ranges of wavelengths.
 18. The device as recitedin claim 1, wherein the biological indicator comprises at least one of arelative percentage, a saturation level, an absolute concentration, arate of change, an index relative to training threshold, and athreshold.
 19. A method configured to determine a biological indicator,the method comprising: emitting a first light from one of at least twoemitters at a first predetermined current; detecting at least a portionof the first emitted light at a detector; obtaining a first calibrationfactor, from the non-transitory storage medium, corresponding to thepredetermined current; generating a first optical density correspondingto the first calibration factor; emitting a second light from anotherone of the at least two emitters at the first predetermined current;detecting at least a portion of the second emitted light at thedetector; obtaining a second calibration factor, from the non-transitorystorage medium, corresponding to the predetermined current; generating asecond optical density corresponding to the second calibration factor;converting the first and second optical density to an effectiveattenuation based on a separation of the one emitter and the anotheremitter; generating a biological indicator from the effectiveattenuation.